search for: cont1

Hello, useR:, Suppose I have two plots made by using contour() function, say Cont1 and Cont2 respectively. They have slightly difference because of the two slightly different data I used. I want to see the difference between them so I want to plot Cont2 on Cont1, are there any methods to plot it without filling the frame of Cont1 totally of Cont2. I mean, how I can integreate...

On Jan 15, 2011, at 8:06 PM, Qingan Li wrote: > [qali at qali llvm-2.8-rev]$ find . -exec grep -n "LLVMCC_EMITIR_FLAG" ./ {} \; > ./projects/test-suite/Makefile.tests:47: -$(LCC) $(CPPFLAGS) $(CFLAGS) $(LOPTFLAGS) $(X_TARGET_FLAGS) -S $< -o $@ $(LLVMCC_EMITIR_FLAG) > ./projects/test-suite/Makefile.tests:51: -$(LCXX) $(CPPFLAGS) $(CXXFLAGS) $(LOPTFLAGS) $(X_TARGET_FLAGS) -S

---------- Forwarded message ---------- From: Qingan Li <ww345ww at gmail.com> Date: 2011/1/19 Subject: Re: [LLVMdev] About test suits Cont1 To: Eric Christopher <echristo at apple.com> *I am sorry for making you confused when I presented my problem.* *1. My steps for the test suit building:* (1) cd /home/qali/Src; * // This is my source directory for all application programs* (2) tar xzf llvm-2.8.tgz; * //...

*[qali at qali llvm-2.8-rev]$ find . -exec grep -n "LLVMCC_EMITIR_FLAG" ./ {} \;* ./projects/test-suite/Makefile.tests:47: -$(LCC) $(CPPFLAGS) $(CFLAGS) $(LOPTFLAGS) $(X_TARGET_FLAGS) -S $< -o $@ $(LLVMCC_EMITIR_FLAG) ./projects/test-suite/Makefile.tests:51: -$(LCXX) $(CPPFLAGS) $(CXXFLAGS) $(LOPTFLAGS) $(X_TARGET_FLAGS) -S $< -o $@ $(LLVMCC_EMITIR_FLAG)

All, I have been reading Dr. Harrell's excellent "Regression Modeling Strategies" book and trying out the exercises. I understand that contrast( ) is used to obtain contrasts between two variables for given levels of other nuisance variables; is there a way to use contrast( ) to obtain, for example, Scheffe confidence intervals / hypothesis tests for many post hoc contrasts at

It appears to be legitimate to include multi-level categorical and continuous variables in defining the model for earth (e.g. y ~ cat + cont1 + cont2) but is it also then possible use categoricals in the predict method using the earth result? I tried but it returns an error which is not very informative. Thanks Chris

hello, i am new to lxc, i have created a lxc container on fedora 19 i created a container rootfs of fedora 19 by using yum --installroot=/containers/test1 --releasever=19 install openssh test1.xml file for container test1 <domain type="lxc"> <name>test1</name> <vcpu placement="static">1</vcpu> <cputune>

*1. I have searched the access/setting of LLVMCC_EMITIR_FLAG in the build directory, recursively, and all the output is what I pasted in last email (just the same to the that in source directory). Maybe the configure failed to do it. My command list for building the test suit is as followings:* *(1) cd ~/SRC_DIR/llvm/projects* *(2) svn co http://llvm.org/svn/llvm-project/test-suite/trunk

On Fri, May 15, 2015 at 5:27 PM, Kaylor, Andrew <andrew.kaylor at intel.com> wrote: > I like the way this sorts out with regard to funclet code generation. > It feels very natural for Windows EH, though obviously not as natural for > non-Windows targets and I think it is likely to block some optimizations > that are currently possible with those targets. > Right, it will

...1 ? 1 ? ?? 1 ? ? 0 ? ?? 0 ? ? 0 ? ? 0 ....... .... ############ data<-read,table("example.txt") data <- as.data.frame(lapply(data, ordered)) ############ Now, suppose I have bigger dataset where some variables are categorical (cat) and others are continuous (cont).. cat1 cat2 cont1 cont2 ...cont10 cat3 cont11....cat 40 cont25? etc. Is there a way to code so that R goes through each variable and orders a variable if it is categorical and leaves a variable alone if it is continuous? Thanks, ?Debs

...ste(inPath,"/t__sd__t.csv", sep="") # sas temporary column definition file coldef <- paste(inPath,"/t__sc__t.csv", sep="") libRef <- obSAS.DataService$AssignLibref("sasds","",inPath,"") # create the content csv file cont1 <- paste("proc contents data=sasds.",inSAS," out=_tmp1(KEEP=NAME TYPE LENGTH VARNUM FORMAT) noprint; run;",sep="") cont2 <- "proc sort data=_tmp1; by varnum; run;" cont3 <- "data _tmp2; set _tmp1; if type=2 then dummy='character'; &quo...

Hello all. I am inexperienced with R and am clumsily trying to work through it for specific multiple imputations Id like to run for my thesis.In running the MIX package, I keep getting an error message regarding the use of the prelim.mix command. Error in as.integer.default(list(alcohol = c(1, 1, 1, 1, 1, 1, 1, 1, 1, : (list) object cannot be coerced to integer I cannot find the

...high p-value..... You do realize that the Kolmogorov tests (and the Kolmogorov-Smirnov extension) assume continuous distributions, so the distribution theory is not valid in this case? S-PLUS does stop you doing this: > ks.gof(o, dist="binomial", size=100, prob=0.25) Problem in not.cont1(ttest = d.test, nx = nx, alt.ex..: For testing discrete distributions when sample size > 50, use the Chi-square test > >Either I am doing something wrong in R, or I am misunderstanding how this > >test should work (both quite possible)... > > > > > >Thanks,...

...ween the first and third level (called here contrast C1) and between the first and the seconda level (called here contrast C2). I used the following procedure: ------------------- reading data from a text file ----------------------- > ar <-read.table("C:/Programmi/R/myworks/contrasti/cont1.txt",header=TRUE) > ar CC GROUP 1 3.0 0 2 3.0 0 3 4.0 0 4 5.0 0 5 6.0 0 6 7.0 0 7 3.0 0 8 2.0 0 9 1.0 1 10 6.0 1 11 5.0 1 12 7.0 1 13 2.0 1 14 3.0 1 15 1.5 1 16 1.7 1 17 17.0...

I've started using lmPerm in order to perform regressions in R. The equation I want to fit has the form: out3 <- lmp(outcome ~ bin1 + bin2 + cont1 + cont2, perm="Exact") Where "outcome" is a non-normally distributed continuous variable, and bin* and cont are binary and continuous regressors (similarly, they are non-normally distributed). Each variable has a length of approx. 110 cases. Here are my questions: This code w...

...ealize that the Kolmogorov tests (and the Kolmogorov-Smirnov >extension) assume continuous distributions, so the distribution theory >is not valid in this case? > >S-PLUS does stop you doing this: > >> ks.gof(o, dist="binomial", size=100, prob=0.25) >Problem in not.cont1(ttest = d.test, nx = nx, alt.ex..: For testing >discrete distributions when sample size > 50, use the > Chi-square test > Thank you for your prompt reply to my bug report. While I agree that the distribution theory for the Kolmogorov tests assumes a continuous distribution, I wou...

...a constructor that may throw: ```llvm %cs = call token @llvm.call.setup(i32 3) %m0 = call i8* @llvm.call.alloc(token %cs, i32 0) invoke void @ctor0(i8* %m0) to label %cont0 unwind label %cleanupCall cont0: %m1 = call i8* @llvm.call.alloc(token %cs, i32 1) invoke void @ctor1(i8* %m1) to label %cont1 unwind label %cleanup0 cont1: %m2 = call i8* @llvm.call.alloc(token %cs, i32 2) invoke void @ctor2(i8* %m2) to label %cont2 unwind label %cleanup1 cont2: call void @use_callsetup(i8* preallocated %m1, i32 13, i8* preallocated %m2,...

...; preds = %catch, %invoke.cont8 call void @_ZN5OuterD1Ev(%class.Outer* %outer) ret void ; Post catch cleanup for lpad, lpad1 ehcleanup10: ; preds = %catch.dispatch invoke void @_ZN5OuterD1Ev(%class.Outer* %outer) to label %invoke.cont11 unwind label %terminate.lpad invoke.cont11: ; preds = %ehcleanup10 br label %eh.resume eh.resume: ; preds = %invoke.cont11 %exn12 = load i8** %exn.slot %sel13 = load i32* %ehselector.slot %lpad.val = insertvalue {...

...cept { try { f(1); Obj o; f(2); } catch (int e) { f(3); try { f(4); } catch (...) { f(5); } } } The IR for __CxxFrameHandler3: define void @foo() personality i32 (...)* @__CxxFrameHandler3 { %e.addr = alloca i32 invoke void @f(i32 1) to label %cont1 unwind label %maycatch.int cont1: invoke void @f(i32 2) to label %cont2 unwind label %cleanup.Obj cont2: call void @~Obj() br label %return return: ret void cleanup.Obj: cleanupblock unwind label %maycatch.int call void @~Obj() resume label %maycatch.int maycatch.int: catchblo...

...@llvm.eh.setehstate(i32 0) invoke void @_ZN5OuterC1Ev(%class.Outer* %outer) to label %invoke.cont unwind label %lpad invoke.cont: call void @llvm.eh.setehstate(i32 1) call void @llvm.eh.setehstate(i32 2) invoke void @_ZN5InnerC1Ev(%class.Inner* %inner) to label %invoke.cont1 unwind label %lpad invoke.cont.1: call void @llvm.eh.setehstate(i32 3) invoke void @_Z14do_inner_thingv() to label %invoke.cont2 unwind label %lpad invoke.cont2: call void @llvm.eh.setehstate(i32 2) invoke void @_ZN5InnerD1Ev(%class.Inner* %inner) to label %invoke.cont...